NDLI: A new genetic based approach to fuzzy controller design and its application

Content Provider	IEEE Xplore Digital Library
Author	Ning Xiong Litz, L.
Copyright Year	1998
Description	Author affiliation: Inst. of Process Autom., Kaiserslautern Univ., Germany (Ning Xiong)
Abstract	One of the major challenges in the current fuzzy control research is the automatic design of multiple input controllers for complex nonlinear systems. This paper presents a new genetic-based scheme to treat this issue: the so-called premise learning approach. We propose to search in the input domain for suitable rule premises. The rule premises are coded in a general way allowing AND- as well as OR-connections of the linguistic terms, in combination with a certain class of input and output fuzzy sets. The rule structure and the fuzzy sets are optimized by the genetic algorithm at the same time. With this new approach a considerable reduction of the number of necessary rules may be expected. This method is used to design a fuzzy controller to balance an inverted pendulum. Simulations as well as results of a real laboratory plant are shown to demonstrate the effectiveness of the new method.
Starting Page	937
Ending Page	941
File Size	542663
Page Count	5
File Format	PDF
ISBN	078034104X
DOI	10.1109/CCA.1998.721596
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-09-04
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy control Fuzzy sets Automatic control Control systems Fuzzy systems Optimization methods Design automation Nonlinear control systems Genetic algorithms Laboratories
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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